Prefrontal theta phase-dependent rTMS-induced plasticity of cortical and behavioral responses in human cortex

Motor cortex excitability states in chronic stroke patients probed by EEG-TMS

OBJECTIVE

In healthy subjects, the trough vs. no-trough phases of the sensorimotor µ-rhythm correspond to high- vs. low-excitability states of the motor cortex (M1). We tested this excitability differentiation in the ipsilesional (iM1) and contralesional M1 (cM1) of chronic stroke patients.

METHODS

19 chronic stroke patients received single-pulse transcranial magnetic stimulation (TMS), separately over the iM1 and cM1, during EEG recordings. High and low M1 excitability states were defined by binning a post-hoc estimate of the µ-phase at TMS delivery. TMS-evoked EEG potentials (TEPs) and time-frequency responses were characterized for excitability states and hemispheres. The motor function of the affected arm was tested by the Fugl-Meyer Assessment Upper Extremity (FMA-UE.

RESULTS

In cM1, TMS at the high- vs. low-excitability state resulted in larger TEP amplitudes and increased post-pulse power in the beta band. In iM1, these modulations were not significant except for post-pulse beta power. This retained excitability differentiation significantly correlated with FMA-UE.

CONCLUSIONS

The degree of excitability differentiation in iM1 depending on phase of the sensorimotor µ-rhythm correlates with individual affected upper extremity motor function.

SIGNIFICANCE

The degree of excitability differentiation in iM1 might serve as a new independent marker of motor recovery.

Cortical Plasticity Induced by Pairing Primary Motor Cortex Transcranial Magnetic Stimulation With Subthalamic Nucleus Magneto-Acoustic Coupling Stimulation

Paired cortical and deep stimulation has the potential to induce enhanced cortical plasticity. Ideally, such stimulation should be noninvasive and precisely controlled. A novel paired stimulation method, combining transcranial magnetic stimulation (TMS) with transcranial magneto-acoustic coupled stimulation (TMAS), named TMS-TMAS, was proposed to achieve such stimulations. Although the primary motor cortex (M1) is stimulated using TMS, the pulsed magnetic field is coupled with a focused ultrasound field to achieve TMAS-based focused electrical stimulation of the subthalamic nucleus (STN) via the magneto-acoustic coupling effect. Cortical plasticity is induced by precisely controlling the timing of magnetic pulse and ultrasound emissions based on spike timing-dependent plasticity (STDP). The experimental system achieved cortical-focused magnetic stimulation with a transverse resolution of 4.3 mm, a longitudinal resolution of 2.8 mm, and a magnetic field intensity of 1.6 T in the M1 region. Additionally, deep-focused electrical stimulation with a transverse resolution of 1.6 mm, a longitudinal resolution of 9.9 mm, and a coupled electric field intensity of 280 mV/m in the STN region was realized. In vivo animal experiments demonstrated that TMS-TMAS enhanced the amplitude of motor evoked potential (MEP) and reduced response latency. Simulation and experimental results confirmed that TMS-TMAS achieves high spatial resolution, noninvasive paired stimulation of the cortex and deep nuclei, and induces enhanced cortical plasticity when the stimulation sequence satisfies the STDP criteria. This method provides a promising approach for noninvasive paired stimulation and is expected to advance brain science research and the rehabilitation of neuropsychiatric disorders involving deep brain structures.

Debunking the Myth of Excitatory and Inhibitory Repetitive Transcranial Magnetic Stimulation in Cognitive Neuroscience Research

Repetitive TMS (rTMS) is a powerful neuroscientific tool with the potential to noninvasively identify brain-behavior relationships in humans. Early work suggested that certain rTMS protocols (e.g., continuous theta-burst stimulation, intermittent theta-burst stimulation, high-frequency rTMS, low-frequency rTMS) predictably alter the probability that cortical neurons will fire action potentials (i.e., change cortical excitability). However, despite significant methodological, conceptual, and technical advances in rTMS research over the past few decades, overgeneralization of early rTMS findings has led to a stubbornly persistent assumption that rTMS protocols by their nature induce behavioral and/or physiological inhibition or facilitation, even when they are applied to nonmotor cortical sites or under untested circumstances. In this Perspectives article, we offer a "public service announcement" that summarizes the origins of this problematic assumption, highlighting limitations of seminal studies that inspired them and results of contemporary studies that violate them. Next, we discuss problems associated with holding this assumption, including making brain-behavior inferences without confirming the locality and directionality of neurophysiological changes. Finally, we provide recommendations for researchers to eliminate this misguided assumption when designing and interpreting their own work, emphasizing results of recent studies showing that the effects of rTMS on neurophysiological metrics and their associated behaviors can be caused by mechanisms other than binary changes in excitability of the stimulated brain region or network. Collectively, we contend that no rTMS protocol is by its nature either excitatory or inhibitory, and that researchers must use caution with these terms when forming experimental hypotheses and testing brain-behavior relationships.

A comparative study to assess synchronisation methods for combined simultaneous EEG and TMS acquisition

Electroencephalography (EEG) combined with transcranial magnetic stimulation (TMS) provides valuable insights into cortical excitability and connectivity but faces challenges including data artefacts, limited spatial resolution, and the need for standardised synchronisation protocols. This study evaluates three TMS-EEG synchronisation paradigms using the Lab Streaming Layer (LSL) to analyse time intervals and latency. Paradigm 1 employs a software-based approach with simultaneous pulses to both EEG and TMS devices. Paradigm 2, another software-based method, transmits a pulse to the TMS device first, followed by the EEG amplifier. Paradigm 3 uses a hardware-based approach where pulses generated by the TMS device are directly routed to the EEG amplifier. Synchronisation was assessed at frequencies of 1, 5, 10, and 20 Hz, with each frequency tested ten times using 100-pulse trains. Results demonstrate that Paradigm 3 provides superior performance, showing narrower distributions, lower time interval error (TIE) and latency values, and higher precision and accuracy. However, it requires a high sample rate from the EEG amplifier and limits additional device integration. Paradigms 1 and 2, while exhibiting greater variability and lower precision, allow for additional device integration and inter-pulse control via LSL. All paradigms achieved low latency and timing error values within acceptable limits for EEG applications, affirming their viability. The choice of synchronisation paradigm has a significant impact on performance, and the current lack of standardisation in TMS-EEG studies presents ongoing challenges. These findings underscore the necessity of selecting an appropriate synchronisation method based on specific study requirements and resources, potentially advancing standardised protocols for TMS and enhancing the reliability of TMS-EEG research.

Response of neuronal populations to phase-locked stimulation: model-based predictions and validation

Modulation of neuronal oscillations holds promise for the treatment of neurological disorders. Nonetheless, conventional stimulation in a continuous open-loop manner can lead to side effects and suboptimal efficiency. Closed-loop strategies such as phase-locked stimulation aim to address these shortcomings by offering a more targeted modulation. While theories have been developed to understand the neural response to stimulation, their predictions have not been thoroughly tested using experimental data. Using a mechanistic coupled oscillator model, we elaborate on two key predictions describing the response to stimulation as a function of the phase and amplitude of ongoing neural activity. To investigate these predictions, we analyze electrocorticogram recordings from a previously conducted study in Parkinsonian rats, and extract the corresponding phase and response curves. We demonstrate that the amplitude response to stimulation is strongly correlated to the derivative of the phase response ([Formula: see text] > 0.8) in all animals except one, thereby validating a key model prediction. The second prediction postulates that the stimulation becomes ineffective when the network synchrony is high, a trend that appeared missing in the data. Our analysis explains this discrepancy by showing that the neural populations in Parkinsonian rats did not reach the level of synchrony for which the theory would predict ineffective stimulation. Our results highlight the potential of fine-tuning stimulation paradigms informed by mathematical models that consider both the ongoing phase and amplitude of the targeted neural oscillation.Significance Statement This study validates a mathematical model of coupled oscillators in predicting the response of neural activity to stimulation for the first time. Our findings also offer further insights beyond this validation. For instance, the demonstrated correlation between phase response and amplitude response is indeed a key theoretical concept within a subset of mathematical models. This prediction can bring about clinical implications in terms of predictive power for manipulation of neural activity. Additionally, while phase dependence in modulation has been previously studied, we propose a general framework for studying amplitude dependence as well. Lastly, our study reconciles the seemingly contradictory views of pathologic hypersynchrony and theoretical low synchrony in Parkinson's disease.

Repetitive magnetic stimulation with iTBS600 induces persistent structural and functional plasticity in mouse organotypic slice cultures

Background

Repetitive transcranial magnetic stimulation (rTMS) is well known for its ability to induce synaptic plasticity, yet its impact on structural and functional remodeling within stimulated networks remains unclear. This study investigates the cellular and network-level mechanisms of rTMS-induced plasticity using a clinically approved 600-pulse intermittent theta burst stimulation (iTBS600) protocol applied to organotypic brain tissue cultures.

Methods

We applied iTBS600 to entorhino-hippocampal organotypic tissue cultures and conducted a 24-hour analysis using c-Fos immunostaining, whole-cell patch-clamp recordings, time-lapse imaging of dendritic spines, and calcium imaging.

Results

We observed long-term potentiation (LTP) of excitatory synapses in dentate granule cells, characterized by increased mEPSC frequencies and spine remodeling over time. c-Fos expression in the dentate gyrus was transient and exhibited a clear sensitivity to the orientation of the induced electric field, suggesting a direction-dependent induction of plasticity. Structural remodeling of dendritic spines was temporally linked to enhanced synaptic strength, while spontaneous firing rates remained stable during the early phase in the dentate gyrus, indicating the engagement of homeostatic mechanisms. Despite the widespread electric field generated by rTMS, its effects were spatially and temporally precise, driving Hebbian plasticity and region-specific spine dynamics.

Conclusions

These findings provide mechanistic insights into how rTMS-induced LTP promotes targeted plasticity while preserving network stability. Understanding these interactions may help refine stimulation protocols to optimize therapeutic outcomes.

Brain state forecasting for precise brain stimulation: Current approaches and future perspectives

Transcranial magnetic stimulation (TMS) has the potential to yield insights into cortical functions and improve the treatment of neurological and psychiatric conditions. However, its reliability is hindered by a low reproducibility of results. Among other factors, such low reproducibility is due to structural and functional variability between individual brains. Informing stimulation protocols with individual neuroimaging data could mitigate this issue, ensuring accurate targeting of structural brain areas and functional brain states in a subject-by-subject fashion. However, this process poses a set of theoretical and technical challenges. We focus on the problem of online functional targeting, which requires collecting electroencephalography (EEG) data, extracting brain states, and using them to trigger TMS in real time. This stream of operations introduces hardware and software delays in the real time set-up, such that brain states of interest may vanish before TMS delivery. To compensate for delays, it is necessary to process the EEG signal in real time, forecast it, and instruct TMS devices to target forecasted - rather than measured - brain states. Recently, this approach has been adopted successfully in a number of studies, opening interesting opportunities for personalised brain stimulation treatments. However, little has been done to explore and overcome the limitations of current forecasting methods. After reviewing the state of the art in brain state-dependent stimulation, we will discuss two broad classes of forecasting methods and their suitability for application to EEG time series. Subsequently, we will review the evidence in favour of data-driven forecasting and discuss its potential contributions to TMS methodology and the scientific understanding of brain dynamics, highlighting the transformative potential of big open datasets.

Closed-loop auditory stimulation targeting alpha and theta oscillations during rapid eye movement sleep induces phase-dependent power and frequency changes

STUDY OBJECTIVES

Alpha and theta oscillations characterize the waking human electroencephalogram (EEG) and can be modulated by closed-loop auditory stimulation (CLAS). These oscillations also occur during rapid eye movement (REM) sleep, but their function here remains elusive. CLAS represents a promising tool to pinpoint how these brain oscillations contribute to brain function in humans. Here we investigate whether CLAS can modulate alpha and theta oscillations during REM sleep in a phase-dependent manner.

METHODS

We recorded high-density EEG during an extended overnight sleep period in 18 healthy young adults. Auditory stimulation was delivered during both phasic and tonic REM sleep in alternating 6-second ON and 6-second OFF windows. During the ON windows, stimuli were phase-locked to four orthogonal phases of ongoing alpha or theta oscillations detected in a frontal electrode.

RESULTS

The phases of ongoing alpha and theta oscillations were targeted with high accuracy during REM sleep. Alpha and theta CLAS induced phase-dependent changes in power and frequency at the target location. Frequency-specific effects were observed for alpha trough (speeding up) and rising (slowing down) and theta trough (speeding up) conditions. CLAS-induced phase-dependent changes were observed during both REM sleep substages, even though auditory evoked potentials were very much reduced in phasic compared to tonic REM sleep.

CONCLUSIONS

This study provides evidence that faster REM sleep rhythms can be modulated by CLAS in a phase-dependent manner. This offers a new approach to investigating how modulation of REM sleep oscillations affects the contribution of this vigilance state to brain function.

Interactions of transcranial magnetic stimulation with brain oscillations: a narrative review

Brain responses to transcranial magnetic stimulation (TMS) can be recorded with electroencephalography (EEG) and comprise TMS-evoked potentials and TMS-induced oscillations. Repetitive TMS may entrain endogenous brain oscillations. In turn, ongoing brain oscillations prior to the TMS pulse can influence the effects of the TMS pulse. These intricate TMS-EEG and EEG-TMS interactions are increasingly attracting the interest of researchers and clinicians. This review surveys the literature of TMS and its interactions with brain oscillations as measured by EEG in health and disease.

Harnessing Brain Plasticity: The Therapeutic Power of Repetitive Transcranial Magnetic Stimulation (rTMS) and Theta Burst Stimulation (TBS) in Neurotransmitter Modulation, Receptor Dynamics, and Neuroimaging for Neurological Innovations

Transcranial magnetic stimulation (TMS) methods have become exciting techniques for altering brain activity and improving synaptic plasticity, earning recognition as valuable non-medicine treatments for a wide range of neurological disorders. Among these methods, repetitive TMS (rTMS) and theta-burst stimulation (TBS) show significant promise in improving outcomes for adults with complex neurological and neurodegenerative conditions, such as Alzheimer's disease, stroke, Parkinson's disease, etc. However, optimizing their effects remains a challenge due to variability in how patients respond and a limited understanding of how these techniques interact with crucial neurotransmitter systems. This narrative review explores the mechanisms of rTMS and TBS, which enhance neuroplasticity and functional improvement. We specifically focus on their effects on GABAergic and glutamatergic pathways and how they interact with key receptors like N-Methyl-D-Aspartate (NMDA) and AMPA receptors, which play essential roles in processes like long-term potentiation (LTP) and long-term depression (LTD). Additionally, we investigate how rTMS and TBS impact neuroplasticity and functional connectivity, particularly concerning brain-derived neurotrophic factor (BDNF) and tropomyosin-related kinase receptor type B (TrkB). Here, we highlight the significant potential of this research to expand our understanding of neuroplasticity and better treatment outcomes for patients. Through clarifying the neurobiology mechanisms behind rTMS and TBS with neuroimaging findings, we aim to develop more effective, personalized treatment plans that effectively address the challenges posed by neurological disorders and ultimately enhance the quality of neurorehabilitation services and provide future directions for patients' care.

Real-time TMS-EEG for brain state-controlled research and precision treatment: a narrative review and guide

Transcranial magnetic stimulation (TMS) modulates neuronal activity, but the efficacy of an open-loop approach is limited due to the brain state's dynamic nature. Real-time integration with electroencephalography (EEG) increases experimental reliability and offers personalized neuromodulation therapy by using immediate brain states as biomarkers. Here, we review brain state-controlled TMS-EEG studies since the first publication several years ago. A summary of experiments on the sensorimotor mu rhythm (8-13 Hz) shows increased cortical excitability due to TMS pulse at the trough and decreased excitability at the peak of the oscillation. Pre-TMS pulse mu power also affects excitability. Further, there is emerging evidence that the oscillation phase in theta and beta frequency bands modulates neural excitability. Here, we provide a guide for real-time TMS-EEG application and discuss experimental and technical considerations. We consider the effects of hardware choice, signal quality, spatial and temporal filtering, and neural characteristics of the targeted brain oscillation. Finally, we speculate on how closed-loop TMS-EEG potentially could improve the treatment of neurological and mental disorders such as depression, Alzheimer's, Parkinson's, schizophrenia, and stroke.

TMS-induced phase resets depend on TMS intensity and EEG phase

Objective. The phase of the electroencephalographic (EEG) signal predicts performance in motor, somatosensory, and cognitive functions. Studies suggest that brain phase resets align neural oscillations with external stimuli, or couple oscillations across frequency bands and brain regions. Transcranial Magnetic Stimulation (TMS) can cause phase resets noninvasively in the cortex, thus providing the potential to control phase-sensitive cognitive functions. However, the relationship between TMS parameters and phase resetting is not fully understood. This is especially true of TMS intensity, which may be crucial to enabling precise control over the amount of phase resetting that is induced. Additionally, TMS phase resetting may interact with the instantaneous phase of the brain. Understanding these relationships is crucial to the development of more powerful and controllable stimulation protocols.Approach.To test these relationships, we conducted a TMS-EEG study. We applied single-pulse TMS at varying degrees of stimulation intensity to the motor area in an open loop. Offline, we used an autoregressive algorithm to estimate the phase of the intrinsicµ-Alpha rhythm of the motor cortex at the moment each TMS pulse was delivered.Main results. We identified post-stimulation epochs whereµ-Alpha phase resetting and N100 amplitude depend parametrically on TMS intensity and are significantversusperipheral auditory sham stimulation. We observedµ-Alpha phase inversion after stimulations near peaks but not troughs in the endogenousµ-Alpha rhythm.Significance. These data suggest that low-intensity TMS primarily resets existing oscillations, while at higher intensities TMS may activate previously silent neurons, but only when endogenous oscillations are near the peak phase. These data can guide future studies that seek to induce phase resetting, and point to a way to manipulate the phase resetting effect of TMS by varying only the timing of the pulse with respect to ongoing brain activity.

TMS-EEG signatures of the effects of transcranial static magnetic field stimulation (tSMS) on cortical excitability

In transcranial static magnetic field stimulation (tSMS), a strong and small magnet placed over the head can modulate cortical functions below the magnet as well as those in the region remote from the magnet. We studied the neuromodulation induced by tSMS using transcranial magnetic stimulation (TMS) combined with simultaneous electroencephalography (EEG) to clarify the neurophysiological underpinnings of tSMS. tSMS or sham stimulation was applied over the left primary motor cortex (M1) for 20 min in 15 healthy subjects. Single pulse TMS was delivered over the left M1 before and after the intervention, while recording EEG. The amplitude around the P30 of the TMS-evoked potentials (TEPs) in the left primary sensorimotor area (SM1) significantly decreased after the real tSMS, and that around the N60 of the TEPs in the right SM1 significantly increased after the real tSMS. In addition, the alpha power of the TMS-induced oscillatory responses (IORs) in the left and right SM1 significantly decreased after the real tSMS. TMS-EEG is a powerful tool for studying local and global cortical reactivity to external stimuli at high temporal resolution. tSMS altered TEPs and IORs both at the stimulated cortex and at the contralateral cortex. These findings would be related to the neurophysiological mechanisms underlying the neuromodulation induced by tSMS.

The contribution of EEG to assess and treat motor disorders in multiple sclerosis

OBJECTIVE

Electroencephalography (EEG) can highlight significant changes in spontaneous electrical activity of the brain produced by altered brain network connectivity linked to inflammatory demyelinating lesions and neuronal loss occurring in multiple sclerosis (MS). In this review, we describe the main EEG findings reported in the literature to characterize motor network alteration in term of local activity or functional connectivity changes in patients with MS (pwMS).

METHODS

A comprehensive literature search was conducted to include articles with quantitative analyses of resting-state EEG recordings (spectrograms or advanced methods for assessing spatial and temporal dynamics, such as coherence, theory of graphs, recurrent quantification, microstates) or dynamic EEG recordings during a motor task, with or without connectivity analyses.

RESULTS

In this systematic review, we identified 26 original articles using EEG in the evaluation of MS-related motor disorders. Various resting or dynamic EEG parameters could serve as diagnostic biomarkers of motor control impairment to differentiate pwMS from healthy subjects or be related to a specific clinical condition (fatigue) or neuroradiological aspects (lesion load).

CONCLUSIONS

We highlight some key EEG patterns in pwMS at rest and during movement, both suggesting an alteration or disruption of brain connectivity, more specifically involving sensorimotor networks.

SIGNIFICANCE

Some of these EEG biomarkers of motor disturbance could be used to design future therapeutic strategies in MS based on neuromodulation approaches, or to predict the effects of motor training and rehabilitation in pwMS.

Closed-Loop Brain Stimulation

In the same way that beauty lies in the eye of the beholder, what a stimulus does to the brain is determined not simply by the nature of the stimulus but by the nature of the brain that is receiving the stimulus at that instant in time. Over the past decades, therapeutic brain stimulation has typically applied open-loop fixed protocols and has largely ignored this principle. Only recent neurotechnological advancements have enabled us to predict the nature of the brain (i.e., the electrophysiological brain state in the next instance in time) with sufficient temporal precision in the range of milliseconds using feedforward algorithms applied to electroencephalography time-series data. This allows stimulation exclusively whenever the targeted brain area is in a prespecified excitability or connectivity state. Preclinical studies have shown that repetitive stimulation during a particular brain state (e.g., high-excitability state), but not during other states, results in lasting modification (e.g., long-term potentiation) of the stimulated circuits. Here, we survey the evidence that this is also possible at the systems level of the human cortex using electroencephalography-informed transcranial magnetic stimulation. We critically discuss opportunities and difficulties in developing brain state-dependent stimulation for more effective long-term modification of pathological brain networks (e.g., in major depressive disorder) than is achievable with conventional fixed protocols. The same real-time electroencephalography-informed transcranial magnetic stimulation technology will allow closing of the loop by recording the effects of stimulation. This information may enable stimulation protocol adaptation that maximizes treatment response. This way, brain states control brain stimulation, thereby introducing a paradigm shift from open-loop to closed-loop stimulation.

Evoked EEG Responses to TMS Targeting Regions Outside the Primary Motor Cortex and Their Test-Retest Reliability

Transcranial magnetic stimulation (TMS)-evoked electroencephalography (EEG) potentials (TEPs) provide unique insights into cortical excitability and connectivity. However, confounding EEG signals from auditory and somatosensory co-stimulation complicate TEP interpretation. Our optimized sham procedure established with TMS of primary motor cortex (Gordon in JAMA 245:118708, 2021) differentiates direct cortical EEG responses to TMS from those caused by peripheral sensory inputs. Using this approach, this study aimed to investigate TEPs and their test-retest reliability when targeting regions outside the primary motor cortex, specifically the left angular gyrus, supplementary motor area, and medial prefrontal cortex. We conducted three identical TMS-EEG sessions one week apart involving 24 healthy participants. In each session, we targeted the three areas separately using a figure-of-eight TMS coil for active TMS, while a second coil away from the head produced auditory input for sham TMS. Masking noise and electric scalp stimulation were applied in both conditions to achieve matched EEG responses to peripheral sensory inputs. High test-retest reliability was observed in both conditions. However, reliability declined for the 'cleaned' TEPs, resulting from the subtraction of evoked EEG response to the sham TMS from those to the active, particularly for latencies > 100 ms following the TMS pulse. Significant EEG differences were found between active and sham TMS at latencies < 90 ms for all targeted areas, exhibiting distinct spatiotemporal characteristics specific to each target. In conclusion, our optimized sham procedure effectively reveals EEG responses to direct cortical activation by TMS in brain areas outside primary motor cortex. Moreover, we demonstrate the impact of peripheral sensory inputs on test-retest reliability of TMS-EEG responses.

Closing the loop in psychiatric deep brain stimulation: physiology, psychometrics, and plasticity

Deep brain stimulation (DBS) is an invasive approach to precise modulation of psychiatrically relevant circuits. Although it has impressive results in open-label psychiatric trials, DBS has also struggled to scale to and pass through multi-center randomized trials. This contrasts with Parkinson disease, where DBS is an established therapy treating thousands of patients annually. The core difference between these clinical applications is the difficulty of proving target engagement, and of leveraging the wide range of possible settings (parameters) that can be programmed in a given patient's DBS. In Parkinson's, patients' symptoms change rapidly and visibly when the stimulator is tuned to the correct parameters. In psychiatry, those same changes take days to weeks, limiting a clinician's ability to explore parameter space and identify patient-specific optimal settings. I review new approaches to psychiatric target engagement, with an emphasis on major depressive disorder (MDD). Specifically, I argue that better engagement may come by focusing on the root causes of psychiatric illness: dysfunction in specific, measurable cognitive functions and in the connectivity and synchrony of distributed brain circuits. I overview recent progress in both those domains, and how it may relate to other technologies discussed in companion articles in this issue.

EEG synchronized left prefrontal transcranial magnetic stimulation (TMS) for treatment resistant depression is feasible and produces an entrainment dependent clinical response: A randomized controlled double blind clinical trial

BACKGROUND

Synchronizing a TMS pulse with a person's underlying EEG rhythm can modify the brain's response. It is unclear if synchronizing rTMS trains might boost the antidepressant effect of TMS. In this first-in-human trial, we demonstrated that a single TMS pulse over the prefrontal cortex produces larger effects in the anterior cingulate depending on when it is fired relative to the individual's EEG alpha phase.

OBJECTIVE/HYPOTHESES

We had three hypotheses. 1) It is feasible to synchronize repetitive TMS (rTMS) delivery to a person's preferred prefrontal alpha phase in each train of every session during a 30-visit TMS depression treatment course. 2) EEG-synchronized rTMS would produce progressive entrainment greater than unsynchronized (UNSYNC) rTMS. And 3) SYNC TMS would have better antidepressant effects than UNSYNC (remission, final Hamilton Depression Rating <10).

METHODS

We enrolled (n = 34) and treated (n = 28) adults with treatment resistant depression (TRD) and randomized them to receive six weeks (30 treatments) of left prefrontal rTMS at their individual alpha frequency (IAF) (range 6-13 Hz). Prior to starting the clinical trial, all patients had an interleaved fMRI-EEG-TMS (fET) scan to determine which phase of their alpha rhythm would produce the largest BOLD response in their dorsal anterior cingulate. Our clinical EEG-rTMS system then delivered the first TMS pulse in each train time-locked to this patient-specific 'preferred phase' of each patient's left prefrontal alpha oscillation. We randomized patients (1:1) to SYNC or UNSYNC, and all were treated at their IAF. Only the SYNC patients had the first pulse of each train for all sessions synchronized to their individualized preferred alpha phase (75 trains/session ×30 sessions, 2250 synchronizations per patient over six weeks). The UNSYNC group used a random firing with respect to the alpha wave. All other TMS parameters were balanced between the two groups. The system interfaced with a MagStim Horizon air-cooled Fig. 8 TMS coil. All patients were treated at their IAF, coil in the F3 position, 120 % MT, frequency 6-13 Hz, 40 pulses per train, average 15-s inter-train interval, 3000 pulses per session. All patients, raters, and treaters were blinded.

RESULTS

In the intent to treat (ITT) sample, both groups had significant clinical improvement from baseline with no significant between-group differences, with the USYNC group having mathematically more remitters but fewer responders. (ITT -15 SYNC; 13 UNSYNC, response 5 (33 %), 1 (7 %), remission 2 (13 %), 6 (46 %). The same was true with the completer sample - 12 SYNC; 12 UNSYNC, response 4, 4 (both 30 %), remission 2 (17 %), 3 (25 %)). The clinical EEG phase synchronization system performed well with no failures. The average treatment session was approximately 90 min, with 30 min for placing the EEG cap and the actual TMS treatment for 45 min (which included gathering 10 min of resting EEG). Four subjects (1 SYNC) withdrew before six weeks of treatment. All 24 completer patients were treated for six weeks despite the trial occurring during the COVID pandemic. SYNC patients exhibited increased post-stimulation EEG entrainment over the six weeks. A detailed secondary analysis of entrainment data in the SYNC group showed that responders and non-responders in this group could be cleanly separated based on the total number of sessions with entrainment and the session-to-session precision of the entrained phase. For the SYNC group only, depression improvement was greater when more sessions were entrained at similar phases.

CONCLUSIONS

Synchronizing prefrontal TMS with a patient's prefrontal alpha frequency in a blinded clinical trial is possible and produces progressive EEG entrainment in synchronized patients only. There was no difference in overall clinical response in this small clinical trial. A secondary analysis showed that the consistency of the entrained phase across sessions was significantly associated with response outcome only in the SYNC group. These effects may not simply be due to how the stimulation is delivered but also whether the patient's brain can reliably entrain to a precise phase. EEG-synchronized clinical delivery of TMS is feasible and requires further study to determine the best method for determining the phase for synchronization.

Toward personalized circuit-based closed-loop brain-interventions in psychiatry: using symptom provocation to extract EEG-markers of brain circuit activity

Symptom provocation is a well-established component of psychiatric research and therapy. It is hypothesized that specific activation of those brain circuits involved in the symptomatic expression of a brain pathology makes the relevant neural substrate accessible as a target for therapeutic interventions. For example, in the treatment of obsessive-compulsive disorder (OCD), symptom provocation is an important part of psychotherapy and is also performed prior to therapeutic brain stimulation with transcranial magnetic stimulation (TMS). Here, we discuss the potential of symptom provocation to isolate neurophysiological biomarkers reflecting the fluctuating activity of relevant brain networks with the goal of subsequently using these markers as targets to guide therapy. We put forward a general experimental framework based on the rapid switching between psychiatric symptom states. This enable neurophysiological measures to be derived from EEG and/or TMS-evoked EEG measures of brain activity during both states. By subtracting the data recorded during the baseline state from that recorded during the provoked state, the resulting contrast would ideally isolate the specific neural circuits differentially activated during the expression of symptoms. A similar approach enables the design of effective classifiers of brain activity from EEG data in Brain-Computer Interfaces (BCI). To obtain reliable contrast data, psychiatric state switching needs to be achieved multiple times during a continuous recording so that slow changes of brain activity affect both conditions equally. This is achieved easily for conditions that can be controlled intentionally, such as motor imagery, attention, or memory retention. With regard to psychiatric symptoms, an increase can often be provoked effectively relatively easily, however, it can be difficult to reliably and rapidly return to a baseline state. Here, we review different approaches to return from a provoked state to a baseline state and how these may be applied to different symptoms occurring in different psychiatric disorders.

Using TMS-EEG to assess the effects of neuromodulation techniques: a narrative review

Over the past decades, among all the non-invasive brain stimulation (NIBS) techniques, those aiming for neuromodulatory protocols have gained special attention. The traditional neurophysiological outcome to estimate the neuromodulatory effect is the motor evoked potential (MEP), the impact of NIBS techniques is commonly estimated as the change in MEP amplitude. This approach has several limitations: first, the use of MEP limits the evaluation of stimulation to the motor cortex excluding all the other brain areas. Second, MEP is an indirect measure of brain activity and is influenced by several factors. To overcome these limitations several studies have used new outcomes to measure brain changes after neuromodulation techniques with the concurrent use of transcranial magnetic stimulation (TMS) and electroencephalogram (EEG). In the present review, we examine studies that use TMS-EEG before and after a single session of neuromodulatory TMS. Then, we focused our literature research on the description of the different metrics derived from TMS-EEG to measure the effect of neuromodulation.

Closed-Loop Deep Brain Stimulation for Psychiatric Disorders

ABSTRACT

Deep brain stimulation (DBS) is a well-established approach to treating medication-refractory neurological disorders and holds promise for treating psychiatric disorders. Despite strong open-label results in extremely refractory patients, DBS has struggled to meet endpoints in randomized controlled trials. A major challenge is stimulation "dosing"-DBS systems have many adjustable parameters, and clinicians receive little feedback on whether they have chosen the correct parameters for an individual patient. Multiple groups have proposed closed loop technologies as a solution. These systems sense electrical activity, identify markers of an (un)desired state, then automatically deliver or adjust stimulation to alter that electrical state. Closed loop DBS has been successfully deployed in movement disorders and epilepsy. The availability of that technology, as well as advances in opportunities for invasive research with neurosurgical patients, has yielded multiple pilot demonstrations in psychiatric illness. Those demonstrations split into two schools of thought, one rooted in well-established diagnoses and symptom scales, the other in the more experimental Research Domain Criteria (RDoC) framework. Both are promising, and both are limited by the boundaries of current stimulation technology. They are in turn driving advances in implantable recording hardware, signal processing, and stimulation paradigms. The combination of these advances is likely to change both our understanding of psychiatric neurobiology and our treatment toolbox, though the timeframe may be limited by the realities of implantable device development.

Manipulating single-unit theta phase-locking with PhaSER: An open-source tool for real-time phase estimation and manipulation

The precise timing of neuronal spiking relative to the brain's endogenous oscillations (i.e., phase-locking or spike-phase coupling) has long been hypothesized to coordinate cognitive processes and maintain excitatory-inhibitory homeostasis. Indeed, disruptions in theta phase-locking have been described in models of neurological diseases with associated cognitive deficits and seizures, such as Alzheimer's disease, temporal lobe epilepsy, and autism spectrum disorders. However, due to technical limitations, determining if phase-locking causally contributes to these disease phenotypes has not been possible until recently. To fill this gap and allow for the flexible manipulation of single-unit phase-locking to on-going endogenous oscillations, we developed PhaSER, an open-source tool that allows for phase-specific manipulations. PhaSER can deliver optogenetic stimulation at defined phases of theta in order to shift the preferred firing phase of neurons relative to theta in real-time. Here, we describe and validate this tool in a subpopulation of inhibitory neurons that express somatostatin (SOM) in the CA1 and dentate gyrus (DG) regions of the dorsal hippocampus. We show that PhaSER is able to accurately deliver a photo-manipulation that activates opsin+ SOM neurons at specified phases of theta in real-time in awake, behaving mice. Further, we show that this manipulation is sufficient to alter the preferred firing phase of opsin+ SOM neurons without altering the referenced theta power or phase. All software and hardware requirements to implement real-time phase manipulations during behavior are available online (https://github.com/ShumanLab/PhaSER).

Pre-Stimulus Power but Not Phase Predicts Prefrontal Cortical Excitability in TMS-EEG

The cortical response to transcranial magnetic stimulation (TMS) has notable inter-trial variability. One source of this variability can be the influence of the phase and power of pre-stimulus neuronal oscillations on single-trial TMS responses. Here, we investigate the effect of brain oscillatory activity on TMS response in 49 distinct healthy participants (64 datasets) who had received single-pulse TMS over the left dorsolateral prefrontal cortex. Across all frequency bands of theta (4-7 Hz), alpha (8-13 Hz), and beta (14-30 Hz), there was no significant effect of pre-TMS phase on single-trial cortical evoked activity. After high-powered oscillations, whether followed by a TMS pulse or not, the subsequent activity was larger than after low-powered oscillations. We further defined a measure, corrected_effect, to enable us to investigate brain responses to the TMS pulse disentangled from the power of ongoing (spontaneous) oscillations. The corrected_effect was significantly different from zero (meaningful added effect of TMS) only in theta and beta bands. Our results suggest that brain state prior to stimulation might play some role in shaping the subsequent TMS-EEG response. Specifically, our findings indicate that the power of ongoing oscillatory activity, but not phase, can influence brain responses to TMS. Aligning the TMS pulse with specific power thresholds of an EEG signal might therefore reduce variability in neurophysiological measurements and also has the potential to facilitate more robust therapeutic effects of stimulation.

Phase matters when there is power: Phasic modulation of corticospinal excitability occurs at high amplitude sensorimotor mu-oscillations

Prior studies have suggested that oscillatory activity in cortical networks can modulate stimulus-evoked responses through time-varying fluctuations in neural excitation-inhibition dynamics. Studies combining transcranial magnetic stimulation (TMS) with electromyography (EMG) and electroencephalography (EEG) can provide direct measurements to examine how instantaneous fluctuations in cortical oscillations contribute to variability in TMS-induced corticospinal responses. However, the results of these studies have been conflicting, as some reports showed consistent phase effects of sensorimotor mu-rhythms with increased excitability at the negative mu peaks, while others failed to replicate these findings or reported unspecific mu-phase effects across subjects. Given the lack of consistent results, we systematically examined the modulatory effects of instantaneous and pre-stimulus sensorimotor mu-rhythms on corticospinal responses with offline EEG-based motor evoked potential (MEP) classification analyses across five identical visits. Instantaneous sensorimotor mu-phase or pre-stimulus mu-power alone did not significantly modulate MEP responses. Instantaneous mu-power analyses showed weak effects with larger MEPs during high-power trials at the overall group level analyses, but this trend was not reproducible across visits. However, TMS delivered at the negative peak of high magnitude mu-oscillations generated the largest MEPs across all visits, with significant differences compared to other peak-phase combinations. High power effects on MEPs were only observed at the trough phase of ongoing mu oscillations originating from the stimulated region, indicating site and phase specificity, respectively. More importantly, such phase-dependent power effects on corticospinal excitability were reproducible across multiple visits. We provide further evidence that fluctuations in corticospinal excitability indexed by MEP amplitudes are partially driven by dynamic interactions between the magnitude and the phase of ongoing sensorimotor mu oscillations at the time of TMS, and suggest promising insights for (re)designing neuromodulatory TMS protocols targeted to specific cortical oscillatory states.